A novel vision based adaptive transmission power control algorithm for energy efficiency in wireless sensor networks employing mobile robots

In a sensor network, there are scenarios when the distance between the transmitting node and the receiving node is not fixed, but varies with time. Such scenarios can arise, for example, when both the transmitting node and receiving node are mounted on mobile robots. Such scenarios could also arise when the transmitting node is fixed (for example, mounted on the ceiling), and the receiving node is mounted on a mobile robot. In such scenarios, it is difficult to predict the appropriate transmission power for successful packet exchanges. A simple strategy is to transmit packets at maximum available power level to ensure successfully transmission, all the time. However, such a strategy would result in a waste of power. We propose a new vision based adaptive transmission power control algorithm for power efficiency in cases when the distance between the transmitter and the receiver varies with time. The proposed algorithm estimates the distance between the transmitter and the receiver by image processing, and accordingly adjusts the transmitting power levels. We tested the algorithm in both noise-free and noisy (when there are obstructions, for ex. people, between the transmitter and the receiver) conditions of the environment on mobile robots using nRF24L01+ transceiver module. We found the algorithm to be robust and able to adjust the transmission power, in real time, to save energy.